The Effectiveness of Pharmacist Interventions on Asthma Management
Bibliographic record
Abstract
Background. In recent years, pharmacists have become more active in patient care and can demonstrate a positive impact on the outcomes of drug therapy in asthma patients. Objective. The primary objective of this systematic review was to assess the impact of asthma improvement strategies used by pharmacists. The secondary objective was to ascertain if these strategies improve the control and other direct outcomes for patients with asthma compared with no intervention. Methods. Electronic databases were searched from January 2006 to February 2012. Data abstracted from publications included publication details, participants/setting, intervention study design, outcome measures, and key findings. Results. Forty-seven studies were initially identified; 8 matched our inclusion criteria. Four were US studies and 4 were Canadian. Published studies provided evidence of the clinical effectiveness of pharmacy services in asthma interventions. The role of pharmacists in disease diagnosis, access to private area for consultation, time, and staff support were highlighted as the key barriers to asthma intervention. Reimbursement for consulting services provided a unique opportunity for pharmacists to provide direct patient care. Conclusion. The review demonstrated the contribution of pharmacy-based services to the monitoring, counseling, and educating in asthma care. The evidence supports the wider provision of asthma intervention through pharmacy services. Well-designed studies on the effectiveness of pharmacists’ interventions to improve outcomes of patients with asthma need to be performed. In addition, further research is needed regarding the contribution of pharmacy services to disease detection as part of local public health strategies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".